Name: AI-Powered Revenue is Here
Uploaded: 2026-02-26T21:37:53.000Z
Duration: 10 min 21 s
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I'm excited today to welcome the founders of Letter AI who are announcing their 40 million Series B round.

Letter AI is an AI native enablement platform, which means we help revenue teams ramp up more quickly with personalized training, coaching, and

also deliver content to engage buyers, ultimately to accelerate the deal cycle.

Who are some of your top customers that are live right now?

Yeah, we have a healthy mix of customers across large enterprises like Lenovo, Adobe, Novo Nordisk, as well as fast growing startups like Plaid and Kong.

What are some of the key use cases that they handle with you across the spectrum?

So, first and foremost, onboarding new team members, making sure that they're productive in about half the time as they were prior to Letter.

Second is through the sales cycle as questions come up as customers request content.

Being able to leverage AI to be able to curate personalized content, to be able to share with the prospect at just the right time.

We have an AI role play and simulation capability as well, so you can practice before you go into a call with an actual buyer and a whole host of new capabilities.

Sort of a simulation for sales folks before they actually do the actual sales conversation.

You don't want to fail in a live conversation, especially with a high stakes prospect.

And so Letter allows you to practice many times before you ever go into that conversation.

So the interesting thing is you guys were here doing YC not too long ago and you already raised a Series B.

You were here at YC just two and a half years ago, but

not many people know that when you went through YC you were a very different company.

What did you learn that that idea didn't work?

And tell us a bit about that initial journey.

Armin, you want to tell the story of Tractatus?

We were basically doing developer tools for generative AI.

And through the process of Y Combinator, we learned very quickly that this was probably not a great idea.

We were trying to sell SAS tools to developers who wanted to write Python code and they would very quickly do prototyping in our platform and then they would just go build it themselves.

And so it wasn't very sticky and we changed the name as well to make it a little bit more memorable.

What was interesting is you landed on this idea, which at the surface seems like it should Be very crowded or very old school.

But Ali you figure out a unique insight during the batch and what was that and what happened?

Because the impressive thing is you were actually able to close Lenovo as a customer in the batch, which is very rare.

And for us, you know, the big insight was really driven by personal experience.

So when I was at Samsara and at Project44, I had used some of the legacy enablement stack.

I remember every single week I would get pinged by a seller at Samsara.

There I was director of engineering for machine learning.

Nothing, no involvement with the sales org by role.

But I'd get pinged by sellers asking, how does this product work?

And I remember saying, hey, why don't you go find all the content we put together, all the learning we put together in our legacy enablement tool.

And the sellers would say, I can't find anything in there, I barely log in.

And so that was kind of light bulb moment number one is there's this really expensive tool which by the way, I couldn't even get a license to because it was so expensive that it's getting very low adoption.

And the second kind of insight here was a lot of times to get leverage and adoption out of enablement tools, you really need to throw a lot of humans at it.

And so humans need to be out there curating content, building content building training.

we found that with AI you could actually tap into existing sources of knowledge and accelerate the process of highly personalized content development.

And speed is what matters in today's day and age for high velocity sales organizations.

And so we thought let's just rethink this entire set of use cases using AI.

And Lenovo actually started through someone I knew there from a previous job who was kind enough to see what we were trying to do.

And it lit a light bulb in his mind and he connected us to the right folks within sales and once they saw what we were building and we took a few steps to make sure we were enterprise ready early on in the journey, that helped us unlock a fairly substantial deal with them that's since grown 10x over the course of the past two years.

So you're telling me there's this gap between basically the product engineering team that's shipping things very fast, especially now in the age of Intelligence product velocity is very fast.

And then there's this gap of translating what is in the product to the sales team, who's not technical, can't necessarily read the code.

But now with AI, you basically supercharge them and automatically produce all the features and sales materials for the team to go at it.

So can you tell us about what are some of these results with some of your customers?

Because you were telling me about this story of a customer that just acquired a company.

And what was that before you and with you?

We have a customer who's a Fortune 100 customer and made an acquisition, a global acquisition, and

was onboarding hundreds of new sellers into the company.

They announced that acquisition internally on a Friday, and

by Monday they had a whole certification in terms of ramping up these new sellers onto the acquiring company's way of doing business.

And what they told us is pre Letter, an exercise like this would have taken them at least a month and tons of folks to get done.

And with Letter, they were able to do it over a weekend with just about two or three folks online.

And that's the kind of impact and velocity that you need today, particularly because the entire industry is evolving so quickly with everything we're seeing happen with LLMs and AI.

So one of the things that happens in this space with sales tools, they tend to be a lot of times sort of just nice to have, but

you found something unique where you've become a core essential.

One of the things we love to hear about LiDAR is particularly compared to the legacy tools where adoption can sometimes be less than 50%, we see customers with close to 100% adoption sellers are going in there every single day, every single week.

And in fact, we heard an anecdote from one customer that if Letter disappeared, there would be a line of folks outside the door of the enablement team banging and asking for it to come back.

And I think a part of how we're making Letter essential is actually related to a new product that we're launching called Letter Compass.

Letter Compass takes the broader enablement content and enablement material that sales teams have historically surfaced to the field.

Things like content, pitch decks, training, certifications, role plays, and

it automatically personalizes it to the book of business that a particular seller or a customer success manager owns.

So now when you log into Letter, it's no longer a generic training on XYZ product.

It's a training that's relevant to the deal that you're pursuing today.

It's insights and follow ups that tap into your conversational intelligence data and CRM data to help you really push the deal forward in a very tangible way.

And I think that moves letter more and more to being an essential tool.

And really it forces you to rethink like what is the future of CRM look like?

Is that really what customer relationship management should be, where AI is presenting insights for you to motivate and move a deal forward?

And we think that's where the world's headed.

So what are some of the interesting things you built on the tech right now, especially with AI that has made all this possible?

Yeah, we've been noticing a lot of our customers are becoming also very AI centric and they're building their own internal tools or even tools that are customer facing to their customers that are using AI like agents and they're now using MCP servers and things like that.

So we've been building our own like letter AI MCP servers.

We have agent to agent protocol that allows our customers either from their web applications, their agents to talk to ours for distributed thinking for example, or their salespeople now are sometimes in cursor and they're doing their own research.

And now they can use a letter AI MCP server to get the content or get answers to the questions they need like that.